The invention relates to a method for the quality control of processes and construction components, through a diagnosis of their sound oscillations during a predetermined time.
The invention is intended primarily for use in the field of quality control and monitoring of machines, motors, installations and production processes. Movements, and the friction associated therewith, as well as the contact of mechanical elements in technical processes cause noises and body conditions vibrations that are characteristic for the respective processes.
Any machine or technical process changes its characteristic vibration behavior as soon as a defect occurs. It is, therefore, important to detect such defects at an early stage in order to prevent damage, and to enable one to assess such vibratory changes objectively and correctly.
It is known that defects in machines and installations make their presence noticable by a change in their characteristic sound and vibratory behavior. The movements in machines and in individual components of these machines send out characteristic body conduction vibrations which provide information about the movements. The vibrations are caused by the contact and friction of the individual machine elements during the machine's movements, and the spring/mass system associated therewith. If the friction or contact, respectively, changes due to defects such as impurities, mechanical damage, loose parts, varying production tolerances, material failure, etc., this in turn causes a change in the acoustic response.
These processes are monitored in many areas of technology by subjective human judgment. Evaluating a defect by way of air conduction, i.e., normal hearing, however, is insufficient. Therefore up until the present, numerous aids have been used to pick up the body conduction vibrations of a monitored machine, such as screw drivers or stethoscopes. Defects are occasionally attended by changes in body conduction vibrations that are audible to the human ear.
Known sound and vibration monitoring methods, as well as human detection, have been predominantly limited to measuring the ambient sound level and the characteristic frequencies of the sound. These sounds are generally picked up with microphones as airborne sound. Air sound measurements are very strongly subject, however, to environmental disturbance (background noise) and therefore can pick up defects in machines only if they produce vibrations which generate frequencies that can be transferred by the air. Thus, only very large changes in the noise and vibration characteristics of the machines can be detected, while fine differences, which make early detection possible, can not be so detected. Sound level measurement is a very strongly integrating method, in which brief vacillations, as found in technical processes, are largely suppressed.
With these methods, it is, therefore, possible to detect only those defects which occur constantly and regularly enough to raise the ambient sound level. Since changes in sound caused by machine defects can be very irregular depending on their cause, the use of frequency analyses to detect such irregular processes is likewise not suitable because, in general, such analyses are dependent upon uniform sound processes which generate characteristic frequencies. Moreover, the frequency analysis of body conduction vibrations is possible only when all conditions of the vibration system, particularly connecting the body conduction receiver, are held exactly constant. This is often extremely difficult under operating conditions.
Since the exact time at which damage will occur in machines cannot be predicted, it is necessary in many cases to constantly monitor the machines to make sure that defects are timely discovered. Therefore, it is desirable to automate the process of sound and vibration diagnosis in order to make it independent of subjective influence. With frequency spectral analyses, as were previously often carried out, this latter objective is still not possible, because the process produces a spectrum that must again be constantly monitored and subjectively interpreted.